Title :
Searching for protein classification features
Author_Institution :
Dept. of Electr. & Comput. Eng., Boise State Univ., ID
Abstract :
A genetic algorithm is used to search for a set of classification features for a protein superfamily which is as unique as possible to the superfamily. These features may then be used for very fast classification of a query sequence into a protein superfamily. The features are based on windows onto modified consensus sequences of multiple aligned members of a training set for the protein superfamily. The efficacy of the method is demonstrated using receiver operating characteristic (ROC) values and the performance of resulting algorithm is compared with other database search algorithms
Keywords :
biology computing; genetic algorithms; pattern classification; proteins; query processing; search problems; sequences; database search algorithm; genetic algorithm; modified consensus sequences; multiple aligned members; protein classification features; protein superfamily; query sequence classification; receiver operating characteristic; Classification algorithms; Data analysis; Evolutionary computation; Frequency; Genetic algorithms; Protein engineering; Sensitivity and specificity; Spatial databases; Web server;
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Conference_Location :
Edinburgh, Scotland
Print_ISBN :
0-7803-9363-5
DOI :
10.1109/CEC.2005.1554744
